How companies can actually adopt AI: what saves time, where to start, and where people have to stay in charge
Hi, I'm Nathan (Netanel) Brumand. I'm an Israeli-American entrepreneur, and this is the first post of The AI-Business Connection.
I have nearly 20 years in business in the US. Most of that time went into the unglamorous parts: hiring, cash flow, answering the phone, showing up when you said you would, and fixing things when they go wrong. Today my focus is one question: how can a business actually use AI to run better, without wasting money, chasing every new tool, or losing the human judgment that customers and teams rely on?
That's what this newsletter is about: AI in business, written for the people who have to make it work.
Why I'm writing this
Almost every business leader I talk to has heard that AI is going to change everything. Far fewer have been told, in plain language, what it can do for their business this quarter, what it will cost them in time and attention, and what can go wrong.
A lot of what's out there is either written for engineers or it's a sales pitch. Leaders get impressive demos that don't fit how their business really works. Meanwhile the real problems haven't changed: customers waiting too long for an answer, leads without follow-up, hours lost to scheduling, reports and paperwork, and too little time left for the work that matters.
I think AI can help with a lot of that. I also think a lot of it is overpromised. My goal here is to sort one from the other, honestly, from the point of view of someone who has run businesses, not just read about them.
Where AI tends to save time
I'll go deeper on each of these in future posts, but these are the areas where I see the most practical value today, in companies of almost any size:
- Responding to customers. Answering common questions and new inquiries quickly, including after hours.
- Follow-up. Reminders, check-ins and next steps that everyone means to send and many people forget.
- Scheduling and coordination. Booking, confirming and rescheduling without a long back-and-forth.
- First drafts. Emails, proposals, job descriptions, website text and internal documents. A person still edits them. Nobody starts from a blank page.
- Summarizing. Turning long threads, meetings, notes or documents into something a decision-maker can read in two minutes.
None of this is magic. It's repetitive work, and repetitive work is where these tools are strongest.
Where to start
Whether you run a five-person shop or lead a team inside a larger company, the advice is the same: don't start with a big transformation project. Start with one task that wastes time every week. Write down how long it takes. Try a tool on it for a few weeks, check the results yourself, and decide whether it really helped. If it did, keep it and pick the next task. If it didn't, drop it without guilt.
Small, boring and measurable beats big and impressive. Strategy matters, but it should be built on what you've actually seen work.
Where a human has to stay in charge
This is the principle that will run through everything I write here: AI can do the preparation. People make the decisions.
An AI tool can draft a reply, suggest a time slot or summarize a request. It shouldn't be the one setting prices, making commitments to a customer, handling an upset client or deciding who to hire. Anything that touches money, promises or a relationship needs a person who reads it and owns it. That's not only about avoiding mistakes. Customers and employees can tell when nobody is really there, and trust is hard to win back.
Honest about the hype
I'll keep this plain. No invented numbers, no "this tool will 10x your business," no pretending something works when it doesn't. When I'm not sure about something, I'll say so. When I try something that fails, I'll tell you about that too, because the mistakes are often more useful than the wins.
What you can expect
Every week, I'll send one post on topics like:
- AI strategy and adoption. How to decide what to try first, how to roll it out, and how to bring a team along.
- Practical AI, task by task. Specific jobs in a business and how AI can (or can't) help with them.
- Small and local businesses. A recurring angle: simple first steps for owners with no tech team and no time to spare.
- Keeping the human in charge. Where to draw the line, and how to check what the tools produce.
- Hype vs. reality. What's ready today, what's not, and how to tell the difference before you pay for it.
- Lessons from the road. What nearly 20 years in business taught me, and the perspective of an Israeli-American entrepreneur building here.
One request
Reply and tell me: what's the biggest time-waster in your business right now? Or, if you've already tried AI at work, what worked and what didn't? I read every reply, and your answers will shape what I write next.
Thanks for being here at the start.
Nathan
More about me and my work: nathanbrumand.com
I'm Nathan (Netanel) Brumand, "Nate" to most people I work with. I write The AI-Business Connection, a weekly newsletter about using AI in business without the hype. The original post is on Substack: https://nathanbrumand.substack.com/p/ai-in-business-without-the-hype. More about me: https://nathanbrumand.com
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